Evidence map›Paper›PMID 34818514›Full record

ArticleNeuron2022

Context-dependent persistency as a coding mechanism for robust and widely distributed value coding.

Ryoma Hattori, Takaki Komiyama

Open access · greenAbstract read
In one paragraph

Article in Neuron, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
3.7field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 45 citations in OpenAlex.

  1. Article
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  4. Meta-learning is expressed through altered prefrontal cortical dynamics.bioRxiv : the preprint server for biology · 2026
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  8. Working memory expands shared task representations in cortex.bioRxiv : the preprint server for biology · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Ryoma HattoriNeurobiology Section, Center for Neural Circuits and Behavior, Department of Neurosciences, and Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA 90093, USA. Electronic address: rhattori0204@gmail.com.
Takaki KomiyamaNeurobiology Section, Center for Neural Circuits and Behavior, Department of Neurosciences, and Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA 90093, USA. Electronic address: tkomiyama@ucsd.edu.
University of California San Diego · US

Funding

Vision BiostatisticsP30EY022589 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LINDA M ZANGWILL · 2012 to 2026
$10.3M
Cortical Control of Motor LearningR01NS091010 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KOMIYAMA, TAKAKI · 2015 to 2024
$3.7M
Cortical plasticity during reinforcement learning - Diversity SupplementR01MH128746 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Takaki Komiyama · 2022 to 2026
$2.3M
Experience-driven plasticity of olfactory bulb odor representationsR01DC014690 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KOMIYAMA, TAKAKI · 2015 to 2019
$1.9M
Experience-driven plasticity of visual circuitsR01EY025349 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KOMIYAMA, TAKAKI · 2015 to 2019
$1.6M
Inter-area communications in a decision-making circuitR03MH120426 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KOMIYAMA, TAKAKI · 2020 to 2020
$158k
NEI NIH HHS P30 EY022589NEI NIH HHS R01 EY025349NIDCD NIH HHS R01 DC014690NIMH NIH HHS R01 MH128746NIMH NIH HHS R03 MH120426NINDS NIH HHS R01 NS091010
6 · The paper itself

Abstract

Task-related information is widely distributed across the brain with different coding properties, such as persistency. We found in mice that coding persistency of action history and value was variable across areas, learning phases, and task context, with the highest persistency in the retrosplenial cortex of expert mice performing value-based decisions where history needs to be maintained across trials. Persistent coding also emerged in artificial networks trained to perform mouse-like reinforcement learning. Persistency allows temporally untangled value representations in neuronal manifolds where population activity exhibits cyclic trajectories that transition along the value axis after action outcomes, collectively forming cylindrical dynamics. Simulations indicated that untangled persistency facilitates robust value retrieval by downstream networks. Even leakage of persistently maintained value through non-specific connectivity could contribute to the brain-wide distributed value coding with different levels of persistency. These results reveal that context-dependent, untangled persistency facilitates reliable signal coding and its distribution across the brain.

Indexed as

LearningReinforcement, PsychologyAnimalsGyrus CinguliMiceNeuronscontext dependentdeep learninghistory codingmachine learningmanifoldpersistent codingrecurrent neural networkreinforcement learningretrosplenial cortexvalue-based decision making

Identifiers

PMID34818514
PMCPMC8813889
OpenAlexW3215374130

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.